GitHub MCP Server

reply_to_review_comment

Respond to pull request review comments by adding replies to existing feedback, facilitating code review discussions on GitHub.

Instructions

Reply to an existing review comment on a pull request.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "owner": "<owner>",
      "repo": "<repo>",
      "pull_number": "<pull_number>",
      "comment_id": "<comment_id>",
      "body": "<body>"
    },
    "name": "reply_to_review_comment"
  }
}

Input Schema

Name	Required	Description
`owner`	Yes	Repository owner
`repo`	Yes	Repository name
`pull_number`	Yes	Pull request number
`comment_id`	Yes	ID of the review comment to reply to
`body`	Yes	Reply text

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Mar 8, 2026

TDQS

B3.1/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'Reply to' implies a mutation/write operation, it doesn't specify permissions required, rate limits, whether replies are editable/deletable, or what the response contains. This is a significant gap for a mutation tool with zero annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero wasted words. It's appropriately sized and front-loaded, directly stating the tool's purpose without unnecessary elaboration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (mutation with 5 parameters), no annotations, and the presence of an output schema (which handles return values), the description is minimally adequate. However, it lacks behavioral context (e.g., permissions, side effects) and usage guidance, leaving gaps for an AI agent to infer correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema fully documents all 5 parameters (owner, repo, pull_number, comment_id, body). The description doesn't add any parameter-specific details beyond what's in the schema, such as format examples or constraints, meeting the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Reply to') and resource ('an existing review comment on a pull request'), providing specific verb+resource. However, it doesn't distinguish this tool from potential siblings like 'create_review_comment' or 'create_issue_comment', which could be used for similar commenting purposes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing comment), exclusions, or compare it to sibling tools like 'create_review_comment' for new comments or 'create_issue_comment' for issue discussions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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